As error correction coding for digital terrestrial broadcasting, there is applied concatenated coding using a Reed-Solomon code (RS code) as outer code and a convolutional code as inner code. On the receiving side, error correction combining Viterbi decoding and Reed-Solomon decoding is performed.
There have been proposed iterative decoding methods which improve error correcting capability by iterating such error correction on the receiving side (see Non-patent Document 1: Meritxell Lamarca et al., “Iterative Decoding Algorithms for RS-Convolutional Concatenated Codes”, 2003 and Non-patent Document 2: Shinichi Murata, “An Iterative-Decoding Method for Concatenated Error-Correcting Codes on ISDB-T”, the IEICE General Conference 2008).
In the technique disclosed in Non-patent Document 1, a soft output method such as SOVA (Soft Output Viterbi Algorithm) decoding or Max-log-MAP decoding is used for decoding of convolutional codes. Further, the soft output method is also employed for the Reed-Solomon decoding.
On the other hand, in the technique disclosed in Non-patent Document 2, feedback values from Reed-Solomon decoding to decoding of convolutional codes are generated depending on success or failure of error correction, for every TSP (Transport stream packet) which is a processing unit of the Reed-Solomon code.
Now, in the technique of Non-patent Document 1, by using the soft decision method which represents whether a received signal is 1 or 0 with a certain range, information obtained from the received signal is used for error correction. Thus, in the receiving device to which the technique of the Non-patent Document 1 is applied, since the soft output method is applied to both decoding of convolutional codes and Reed-Solomon decoding, the circuit scale becomes large. Accordingly, it is difficult to be applied as it is to ISDB-T (Integrated Services Digital Broadcasting-Terrestrial) which is digital terrestrial broadcasting in Japan.
On the other hand, in the technique of Non-Patent Document 2, circuit structures are simplified in consideration of application to ISDB-T. However, there is no specific description about how to generate likelihood ratio information to be added to or subtracted from metric in the decoding of convolutional codes in order to feed back information on success/failure of error correction decoding to the decoding of convolutional codes.